Dynamic Speckle Research Articles

Poincare vector correlations to estimate polarization dynamics in the laser speckle

We propose and experimentally demonstrate a new method to measure the spatial polarization dynamics of laser speckles. This is realized by using the concept of the Poincare vector correlations and experimentally measured Stokes parameters. Two-point correlations of the Stokes parameters offer a new and stable experimental technique to determine the Poincare vector correlations and characterize the polarization fluctuations of the laser speckle. The use of two-point Stokes correlations in the evaluation of spatial polarization dynamics offers a new method and the performance of this technique is tested by evaluating the spatial polarization dynamics of three different cases of the laser speckles. Experimental results are also tested and compared with the simulations results and good agreement between simulation and experimental results confirm the accuracy and usefulness of our technique in the characterization of the polarization dynamics.

Imaging the vasculature of a beating heart by dynamic speckle: the challenge of a quasiperiodic motion.

The spatial and temporal evolution of the field backscattered by a beating heart while illuminated with a coherent light reveals its macro- and microvascularization in real time. To perform these vascularization images, we use a recently published method of laser speckle imaging, based on the selective detection of spatially depolarized speckle field that is mainly generated by multiple scattering. We consider the calculation of the speckle contrast, by a spatial or temporal estimation. We show that the signal-to-noise ratio of the observed vascular structure can be noticeably increased by a postprocessing method implying the calculation of a motion field that allows the selection of similar frames extracted from different heartbeat periods. This later optimization reveals vascular microstructures with a spatial resolution of the order of .

Prediction of motion artifacts caused by translation in handheld laser speckle contrast imaging.

In handheld laser speckle contrast imaging (LSCI), motion artifacts (MA) are inevitable. Suppression of MA leads to a valid and objective assessment of tissue perfusion in a wide range of medical applications including dermatology and burns. Our study shines light on the sources of these artifacts, which have not yet been explored. We propose a model based on optical Doppler effect to predict speckle contrast drop as an indication of MA. We aim to theoretically model MA when an LSCI system measuring on static scattering media is subject to translational displacements. We validate the model using both simulation and experiments. This is the crucial first step toward creating robustness against MA. Our model calculates optical Doppler shifts in order to predict intensity correlation function and contrast of the time-integrated intensity as functions of applied speed based on illumination and detection wavevectors. To validate the theoretical predictions, computer simulation of the dynamic speckles has been carried out. Then experiments are performed by both high-speed and low-framerate imaging. The employed samples for the experiments are a highly scattering matte surface and a Delrin plate of finite scattering level in which volume scattering occurs. An agreement has been found between theoretical prediction, simulation, and experimental results of both intensity correlation functions and speckle contrast. Coefficients in the proposed model have been linked to the physical parameters according to the experimental setups. The proposed model provides a quantitative description of the influence of the types of illumination and media in the creation of MA. The accurate prediction of MA caused by translation based on Doppler shifts makes our model suitable to study the influence of rotation. Also the model can be extended for the case of dynamic media, such as live tissue.

Spatial-temporal correlations in the speckle pattern for the characterization of cellular motion within a 3D object.

Dynamic light scattering analysis has been demonstrated recently to be a promising tool for the assessment of structural changes taking place inside opaque tissue samples. Specifically, quantification of velocity and direction of cellular motion inside spheroids and organoids has attracted much attention as a potent indicator in personalized therapy research. Here, we propose a method for the quantitative extraction of cellular motion, velocity, and direction, by applying a concept of speckle spatial-temporal correlation dynamics. Numerical simulations and experimental results obtained on phantom and biological spheroids are presented.

Consideration of Laser Speckle Contrast Analysis for Shunt Management

In hemodialysis, normal venipuncture cannot deliver large amounts of blood, so about 90% of patients make an arteriovenous anastomosis called an internal shunt. In addition, since dialysis is performed multiple times a week, frequent puncture and pressure hemostasis are required. As a result, blood vessels are stressed, resulting in stenosis and occlusion. In order to detect and treat such shunt troubles at an early stage, daily shunt management is important. Laser speckle contrast analysis is of interest in the field of visualization of the hemodynamics of living tissues. In this study, the relationship between the flow rate and the contrast value was investigated by a technique for quantifying the amount of change in the dynamic speckle pattern.

Noise analysis in outdoor dynamic speckle measurement.

The dynamic speckle method (DSM) is an effective tool for the estimation of speed of processes. The speed distribution is encoded in a map built by statistical pointwise processing of time-correlated speckle patterns. For industrial inspection, the outdoor noisy measurement is required. The paper analyzes the efficiency of the DSM in the presence of environmental noise as phase fluctuations due to the lack of vibration isolation and shot noise due to ambient light. The usage of normalized estimates for the case of non-uniform laser illumination is studied. The feasibility of the outdoor measurement has been proven by numerical simulations of noisy image capture and real experiments with test objects. Good agreement has been demonstrated in both the simulation and experiment between the ground truth map and the maps extracted from noisy data.

Assessment of the Use of Infrared Laser for Dynamic Laser Speckle (DLS) Technique

Dynamic laser speckle (DLS) analysis is a very sensitive technique to measure biological activity within samples. In agriculture, the technique is applied to monitor seed germination, but external light, water content, and pigments affect the measurements. DLS systems use visible light sources, typically red lasers, which may exacerbate their influences. The main objective of this work is to assess whether infrared (IR) lasers improve the robustness of DLS measurements in seed germination applications. We develop a system where DLS analysis can be performed simultaneously on visible and IR light. Using the system, we quantify how the DLS signal is affected by pigments and scattering. The results show that the use of IR light reduces the variability of the measurements acquired. DLS systems based on IR light appear to be less sensitive to pigments, and the greater penetration of IR light into samples, which is due to reduced scattering, may contribute to the signal collected being correlated to relevant biological processes within the inner tissue. Additionally, water activity provides less influence on the DLS signal when an IR laser is used. These findings support the wider use of IR lasers in DLS-based instruments for applications in biological samples.

Spatiotemporal analysis of speckle dynamics to track invisible needle in ultrasound sequences using convolutional neural networks: a phantom study.

Accurate needle placement into the target point is critical for ultrasound interventions like biopsies and epidural injections. However, aligning the needle to the thin plane of the transducer is a challenging issue as it leads to the decay of visibility by the naked eye. Therefore, we have developed a CNN-based framework to track the needle using the spatiotemporal features of the speckle dynamics. There are three key techniques to optimize the network for our application. First, we used Gunnar-Farneback (GF) as a traditional motion field estimation technique to augment the model input with the spatiotemporal features extracted from the stack of consecutive frames. We also designed an efficient network based on the state-of-the-art Yolo framework (nYolo). Lastly, the Assisted Excitation (AE) module was added at the neck of the network to handle the imbalance problem. Fourteen freehand ultrasound sequences were collected by inserting an injection needle steeply into the Ultrasound Compatible Lumbar Epidural Simulator and Femoral Vascular Access Ezono test phantoms. We divided the dataset into two sub-categories. In the second category, in which the situation is more challenging and the needle is totally invisible, the angle and tip localization error were 2.43 ± 1.14° and 2.3 ± 1.76mm using Yolov3+GF+AE and 2.08 ± 1.18° and 2.12 ± 1.43mm using nYolo+GF+AE. The proposed method has the potential to track the needle in a more reliable operation compared to other state-of-the-art methods and can accurately localize it in 2D B-mode US images in real time, allowing it to be used in current ultrasound intervention procedures.

Spatiotemporal characteristics of dynamic speckle from a 3D target in atmospheric turbulence

Spatiotemporal correlation function is the basic characteristic of dynamic laser speckle and the basis of various applications. The correlation function of the speckle intensity from a 3D target in turbulent atmosphere is derived based on the model of random phase screen and Fresnel Kirchhoff Diffraction Formula, and a fast algorithm based on FFT is developed. The particularity of dynamic speckle in turbulence is numerically analyzed and discussed. The results show that the speckle intensity fluctuates at two independent scales both in space and time domain, which are affected by target size and atmospheric turbulence respectively. In particular, the time scale caused by turbulence is also affected by the target translating velocity and the wind direction. The theory and algorithm developed in this paper can play important roles in applications of laser speckle such as remote detection in atmospheric environment.

A novel computational method for dynamic laser speckle and its application to analyze water activity during photosynthesis in papaya leaf

Dynamic Laser Speckle (DLS) images are processed under different computational methods to extract activity map and numerical information of the activity present in the sample. Some existing methods include GD, Fujii, which provides the activity map, and IM, AVD, which numerically quantifies the activity. However, there is hardly a method that simultaneously provides speckle activity map linked with a numerical value. It takes much time to process with different methods for graphical and numerical information about the speckle activity. In this work, a new method has been proposed, which provides the speckle activity map associated with a numerical information for DLS analysis. We have found that both the graphical and numerical results obtained from the proposed method are in good agreement with other existing methods. In another experiment of Biospeckle imaging of papaya leaf subjected under different PAR intensities, we have found that the average frequency (represents the biospeckle activity) of papaya leaf increases as the photosynthesis rate increases. Furthermore, this method takes less computational time (0.70 ± 0.021 s) to process data compared to GD (1.89 ± 0.012 s), Fujii (0.75 ± 0.042 s), and IM & AVD (1.1 ± 0.017 s).

Оптическая диффузионная диагностика эволюционирующих полимерных пен

Various approaches to the optical diagnostics of evolving polymer foams formed as a result of a decrease in the external pressure according to a given scenario in the "polymer - supercritical fluid" systems are considered.Formed polymer foams are considered as a material platform for the creation of scaffolds for biomedical applications. Diagnostics of the current state of the foam was carried out by statistical analysis of the spatiotemporal fluctuations of the probe laser radiation,multiple scattered in the volume of the evolving foam, or by analyzing the fluorescent response during foaming of the "polymer-fluorophore" mixture, pumped by laser radiation in the absorption band of the fluorophore. A relationship has been established between the average lifetime of dynamic speckles in scattered laser light and a generalized parameter characterizing the foam expansion dynamics. It was also found that the waveguide effect in the walls of the formed pores has a significant influence on the fluorescent response of the evolving foam, leading to an increase in the characteristic dwell time of fluorescence radiation in the walls and, accordingly, to an increase in the contribution of the induced component to the fluorescent response.

Optical diffusion diagnostics of evolving polymer foams

Various approaches to the optical diagnostics of evolving polymer foams formed as a result of a decrease in the external pressure according to a given scenario in the "polymer-supercritical fluid" systems are considered.Formed polymer foams are considered as a material platform for the creation of scaffolds for biomedical applications. Diagnostics of the current state of the foam was carried out by statistical analysis of the spatiotemporal fluctuations of the probe laser radiation,multiple scattered in the volume of the evolving foam, or by analyzing the fluorescent response during foaming of the "polymer-fluorophore" mixture, pumped by laser radiation in the absorption band of the fluorophore. A relationship has been established between the average lifetime of dynamic speckles in scattered laser light and a generalized parameter characterizing the foam expansion dynamics. It was also found that the waveguide effect in the walls of the formed pores has a significant influence on the fluorescent response of the evolving foam, leading to an increase in the characteristic dwell time of fluorescence radiation in the walls and, accordingly, to an increase in the contribution of the induced component to the fluorescent response. Keywords: fluorescent response, speckle correlometry, polylactide, foaming, supercritical carbon dioxide.

Improvement of activity level detection in dynamic speckle patterns with fuzzy logic operators

In this work, the design of a multi-descriptor model is proposed to improve the identification of activity levels in dynamic laser speckle (DLS) image sequences. Fuzzy predicates evaluated with operators of different logic systems were used. The model considers both temporal and spatial effects of the DLS phenomenon. Experiments were carried out to characterize the drying times of a sample painted with water-based paint, illuminated with a coherent light, whose image sequences were captured with a CCD camera. To assess the improvement of the proposed model with respect to single descriptors, the Kruskal–Wallis test and the silhouette index were used. The compensatory logic operators achieved the best results to improve the discrimination of the activity levels, according to the different drying times in the dynamic laser speckle sequences.

Dynamic speckle imaging with SVD compression

Dynamic speckle imaging (DSI) of areas with different speed of processes ongoing in industrial or biological objects relies on statistical processing of a large number of images of the speckle patterns formed on the objects surface under laser illumination. The DSI visualizes the speed spatial distribution as an activity map. We propose compression of the raw DSI data by applying singular value decomposition (SVD). A specific feature of speckle images for DSI is lack of a structure with areas of close intensity values. The gain from the direct SVD application may be modest in cases when a great number of non-zero singular values is needed to build an activity map comparable in quality to the ground truth map from bitmap images. For higher compression, we propose SVD to be applied to the 2D arrays containing the differences between the successive images. The SVD compression has been verified by using synthetic and experimental data.

Model of dynamic speckle evolution for evaluating laser speckle contrast measurements of tissue dynamics.

We introduce a dynamic speckle model (DSM) to simulate the temporal evolution of fully developed speckle patterns arising from the interference of scattered light reemitted from dynamic tissue. Using this numerical tool, the performance of laser speckle contrast imaging (LSCI) or speckle contrast optical spectroscopy (SCOS) systems which quantify tissue dynamics using the spatial contrast of the speckle patterns with a certain camera exposure time is evaluated. We have investigated noise sources arising from the fundamental speckle statistics due to the finite sampling of the speckle patterns as well as those induced by experimental measurement conditions including shot noise, camera dark and read noise, and calibrated the parameters of an analytical noise model initially developed in the fundamental or shot noise regime that quantifies the performance of SCOS systems using the number of independent observables (NIO). Our analysis is particularly focused on the low photon flux regime relevant for human brain measurements, where the impact of shot noise and camera read noise can become significant. Our numerical model is also validated experimentally using a novel fiber based SCOS (fb-SCOS) system for a dynamic sample. We have found that the signal-to-noise ratio (SNR) of fb-SCOS measurements plateaus at a camera exposure time, which marks the regime where shot and fundamental noise dominates over camera read noise. For a fixed total measurement time, there exists an optimized camera exposure time if temporal averaging is utilized to improve SNR. For a certain camera exposure time, photon flux value, and camera noise properties, there exists an optimized speckle-to-pixel size ratio (s/p) at which SNR is maximized. Our work provides the design principles for any LSCI or SCOS systems given the detected photon flux and properties of the instruments, which will guide the experimental development of a high-quality, low-cost fb-SCOS system that monitors human brain blood flow and functions.

Single-shot temporal speckle correlation imaging using rolling shutter image sensors

We propose a single-shot wide-field imaging method that maps local temporal intensity decorrelations of dynamic speckle fields. Our method, named rolling shutter speckle imaging (RSSI), utilizes short time intervals between each row of a rolling shutter complementary metal–oxide–semiconductor (RS-CMOS) image sensor to discern fast temporal changes in the speckle field, which otherwise requires sequential measurements with high-speed cameras. RSSI generates elongated speckle patterns on an RS-CMOS image sensor and quantifies temporal decorrelations of speckle fields from row-by-row intensity correlations (RICs) within a single image. To quantify the local speckle decorrelation times of dynamic scattering media, we derived a theoretical model for RIC and verified the model using numerical simulations and flow-phantom experiments. Further, our in vivo imaging results show that RSSI can map the flow rate distributions in cerebral blood vessels with the correction of static scattering in the tissue, demonstrating that RSSI is a powerful and cost-effective imaging tool for in vivo quantitative blood flow measurements.

Statistical analysis of curing phenomenon of an epoxy adhesive

Dynamic speckle imaging is one of the powerful optical techniques used for investigating the dynamical processes of biological as well as industrial materials. It is a cost effective technique and also non-invasive in nature. It possesses high temporal and spatial resolution. This paper reports the application of certain numerical algorithms for extracting the information regarding the curing process of an epoxy adhesive. Time evolution of speckle images were analyzed using statistical methods such as Normalized 2 dimensional Cross-correlation and Inertia moment. The Inertia moment was found to decrease and correlation coefficient was found to increase due to the fall in activity that resulted by the curing phenomenon. The curing time of epoxy is obtained as five minutes which is in accordance with the company literature.

Sampling rate in the dynamic speckle analysis

Dynamic laser speckle and its biological version (biospeckle laser) have been used in many areas of knowledge. Its non-invasive approach allows the application in advantage regarding those that need contact or damage the analyzed sample. However, one needs the sharp adjust of the image acquiring and processing. In this article, we show how the variation of sampling rate in a dynamic speckle analysis affects the value of dynamic speckle indexes concerning the absolute value of the differences index, the temporal speckle standard deviation index, and the temporal speckle mean index. We show that the dynamic speckle index value changes its maximum excursion with the variation of sampling rate, affected directly by the camera's time integration (time of exposure). We highlight the importance of knowing the frequency band of the analyzed phenomenon and its signal to choose the appropriate sampling rate, with the recommendation of using the lowest sampling rate possible—without compromise the speckle grains—to obtain an acceptable maximum excursion and an illumination level with a good signal–noise ratio. The results will help those who work with the phenomenon/technique to enhance their analysis tailoring the set up and yielding reliable results, since the optical method demands a rigorous bias of the image acquiring and processing.

Use of speckle laser to identify canopy variations in plants subjected to ultra-high diluted substances

The reaction of plants to ultra-high dilute substances (UHD) is well known, however, the signaling of the immediate effect still doesn't have a widely accepted methodology. The objective of this experiment was to use non-destructive sampling to find signs of UHD soon after application to plants. The control consisted of untreated purslane [Pilea microphylla (L.) Liebm] plants and imaged with a digital camera Mobius (CMOS 1270x720 pixels) directed at a laser beam (±680 nm) emitted over the plant canopy for 220 seconds, with 6-second intervals. Then, the same plants were treated with Fluoricum acidum 30CH (Fl. ac. 30), and ten minutes later, new images of the leaves were taken to verify the possible existence of reaction patterns of the plants generated by Biospeckle Laser (1,2). Several types of imaging were performed to choose the image pattern, and the NIR type was chosen, generated by the Mobius camera connected directly to a laptop. The images were treated using the THSP algorithm, which generated data to compare the variation of pixel intensity with and without the presence of UHD. Research has shown that "Fl. ac. 30" is identified in purslane plants soon after application and this sign persists for at least 180 minutes after application, with a significant difference from the control at the 1% probability level.
 Keywords: computational vision; homeopathy signal; dynamic laser speckle

Machine Learning for analysis of speckle dynamics: quantification and outlier detection

X-ray photon correlation spectroscopy (XPCS) provides an understanding of complex dynamics in materials that are tied to their synthesis, properties, and behaviors. Analysis of XPCS data for dynamics that are far from equilibrium is labor intense and often can impede the discovery process, especially in experiments with high collection rates. Moreover, binning and averaging, involved in the analysis for alleviating poor signal-to-noise ratio, leads to a loss of temporal resolution and the accumulation of systematic error for the parameters quantifying the dynamics. Here, we integrate a denoising autoencoder model into workflows for the analysis of nonequilibrium two-time intensity-intensity correlation functions. Noise reduction allows for extracting the parameters that characterize the sample's dynamics with the temporal resolution limited only by frame rates. Not only does it improve the quantitative usage of the data, but it also creates the potential for automating the analytical workflow, which is a key to high-throughput or autonomous XPCS experiments. Various approaches for the uncertainty quantification and extension of the model for anomalies' detection are discussed.